Apparatus and method for angular resolution inspection of lidar device

Abstract

The present invention provides a method for angular resolution inspection of a light detection and ranging (LiDAR) device, the method comprising the steps of: preparing and arranging an inspection target LiDAR device and a target; rotating the inspection target LiDAR device by rotation steps, and causing the inspection target LiDAR device to record at least one frame at each of the rotation steps and generate a point cloud on the basis of the recorded frames; selecting a plurality of data points within the generated point cloud; acquiring intensity data at at least some of the rotation steps for each selected data point; calculating an average value of the acquired intensity data for each of the data points; selecting an upper proximity value and a lower proximity value relative to the calculated average value among the acquired intensity data for each data point; calculating a corresponding angle corresponding to the average value for each data point by using linear regression analysis on the selected upper proximity value and lower proximity value and the rotation angles at each rotation step for each of the upper proximity value and the lower proximity value; and determining angular resolution of the inspection target LiDAR device on the basis of the corresponding angle calculated for each of the data points and the number of data points located between the selected data points in the point cloud.

Description

Inspection device and method for each resolution of a LiDAR device

[0001] The present invention relates to a lidar device. More specifically, the present invention relates to performance testing of a lidar device, for example, testing of each resolution of a lidar device.

[0002] LiDAR devices are important sensors for detecting the shape and distance of objects and are utilized in various industrial fields, such as autonomous vehicles, drones, and robots. LiDAR devices scan the surrounding environment using light and generate a point cloud, which is a set of data points in 3D space, based on the collected data. At this time, the quality of the point cloud depends significantly on the performance of the LiDAR device. One such performance characteristic of a LiDAR device is Angular Resolution.

[0003] Angular resolution refers to the minimum angular difference that a LiDAR device can detect within a specific angle, and LiDAR devices with high angular resolution can detect objects in detail. Therefore, the angular resolution of a LiDAR device can serve as an important indicator for evaluating its performance.

[0004] As a method for inspecting each resolution of a LiDAR device, a method utilizing the edge of a single target or the edge formed between multiple targets may be used. Specifically, light is emitted to the aforementioned edge, and depth information (distance information) included in a point cloud calculated based on reflected light reflected from the vicinity of the edge may be utilized.

[0005] However, there is a problem in that depth information near the edges has high discontinuity and low accuracy. This problem can occur due to the method by which the LiDAR device generates depth information through a superpixel composed of multiple photodetectors.

[0006] In addition, when forming edges using multiple targets, there is a problem where errors resulting from the placement of multiple targets overlap.

[0007] Therefore, in addition to depth information, there is a need for parameters that can serve as a standard for inspecting each resolution of the LiDAR device.

[0008] In addition, there is a need for a method to inspect each resolution of a LiDAR device without using multiple targets.

[0009] The objective of the present invention is to provide a device and method for inspecting each resolution of a lidar device using depth information within a point cloud calculated by the lidar device and different data.

[0010] The objective of the present invention is to provide a device and method for inspecting each resolution of a LiDAR device using a single target.

[0011] To solve the problem of the present invention, in a method for inspecting each resolution of a LiDAR (Light Detection And Ranging) device, the method comprises the steps of: preparing and placing a LiDAR device to be inspected and a target; rotating the LiDAR device to be inspected in rotation steps, causing the LiDAR device to be inspected to record at least one frame in each of the rotation steps, and calculating a point cloud based on the recorded frame; selecting a plurality of data points within the calculated point cloud; acquiring intensity data in at least some of the rotation steps for each of the selected data points; calculating an average value of the acquired intensity data for each of the data points; selecting an upper proximity value and a lower proximity value for the calculated average value among the acquired intensity data for each of the data points; and calculating a corresponding angle corresponding to the average value through linear regression analysis of the selected upper proximity value and the lower proximity value and the rotation angle in the rotation step for each of the upper proximity value and the lower proximity value. The present invention provides a method for inspecting each resolution of a lidar device, comprising the step of determining each resolution of the lidar device to be inspected based on the corresponding angle calculated for each of the data points and the number of data points located between the selected data points within the point cloud.

[0012] To solve the problem of the present invention, a method for inspecting each resolution of a LiDAR (Light Detection And Ranging) device comprises: a step of preparing and placing a LiDAR device to be inspected and a target; a step of rotating the LiDAR device to be inspected in rotation steps, causing the LiDAR device to be inspected to record at least one frame in each of the rotation steps, and calculating a point cloud based on the recorded frame; a step of selecting a plurality of data points within the calculated point cloud; a step of acquiring intensity data in at least some of the rotation steps for each of the selected data points; a step of generating an angle-intensity graph for each of the data points based on the acquired intensity data and the rotation angle in the rotation step in which the intensity data was acquired; and a step of performing sigmoid fitting on the generated angle-intensity graph. A method for inspecting each resolution of a lidar device is provided, comprising: a step of calculating a similarity-based aligned distance between the sigmoid-fitted angle-intensity graphs for each of the data points through a similarity evaluation of the sigmoid-fitted angle-intensity graphs; and a step of determining each resolution of the lidar device to be inspected based on the similarity-based aligned distance and the number of data points located between the selected data points within the point cloud.

[0013] According to one embodiment of the present invention, the target comprises a first portion and a second portion, and the reflectance of each of the first portion and the second portion may be different from each other.

[0014] According to one embodiment of the present invention, the target may have a linear boundary formed at the portion where the first portion and the second portion meet each other.

[0015] According to one embodiment of the present invention, the first part and the second part are arranged in a horizontal or vertical direction, and when the first part and the second part are arranged in a horizontal direction, the linear boundary is formed in a vertical direction, and when the first part and the second part are arranged in a vertical direction, the linear boundary can be formed in a horizontal direction.

[0016] According to one embodiment of the present invention, the intensity data included in the data point calculated based on light reflected from the first part may be different from the intensity data included in the data point calculated based on light reflected from the second part.

[0017] According to one embodiment of the present invention, the target is configured in the form of a flat plate, and the first part and the second part can form the target as a single unit.

[0018] To solve the problem of the present invention, a system for inspecting the resolution of a LiDAR (Light Detection And Ranging) device comprises: an inspection device for determining the resolution of the LiDAR device to be inspected; and a target for reflecting light emitted by the LiDAR device to be inspected; wherein the inspection device comprises: a support member for the LiDAR device to be inspected for supporting the LiDAR device to be inspected; a rotation adjustment unit for rotating the support member for the LiDAR device to be inspected and the LiDAR device to be inspected in rotational steps; and a processor unit for controlling the operation of the LiDAR device to be inspected and the rotation adjustment unit, and for determining the resolution of the LiDAR device to be inspected based on intensity data included in a point cloud calculated by the LiDAR device to be inspected.

[0019] According to one embodiment of the present invention, the processor unit comprises the steps of: causing the rotation adjustment unit to rotate the inspection target lidar device in the rotation steps, causing the inspection target lidar device to record at least one frame in each of the rotation steps, and calculating the point cloud based on the recorded frame; selecting a plurality of data points within the calculated point cloud; acquiring intensity data in at least some of the rotation steps for each of the selected data points; calculating the average value of the acquired intensity data for each of the data points; selecting an upper proximity value and a lower proximity value for the calculated average value among the acquired intensity data for each of the data points; and calculating a corresponding angle corresponding to the average value through linear regression analysis of the rotation angle in the rotation step for each of the selected upper proximity value and the lower proximity value and each of the upper proximity value and the lower proximity value. It may be for performing the step of determining each resolution of the inspected lidar device based on the corresponding angle calculated for each of the data points and the number of data points located between the selected data points within the point cloud.

[0020] According to one embodiment of the present invention, the processor unit comprises the steps of: causing the rotation adjustment unit to rotate the inspection target lidar device in the rotation steps, causing the inspection target lidar device to record at least one frame in each of the rotation steps, and calculating the point cloud based on the recorded frame; selecting a plurality of data points within the calculated point cloud; acquiring intensity data in at least some of the rotation steps for each of the selected data points; generating an angle-intensity graph for each of the data points based on the acquired intensity data and the rotation angle in the rotation step in which the intensity data was acquired; performing sigmoid fitting on the generated angle-intensity graph; and calculating a similarity-based aligned distance between the sigmoid-fitted angle-intensity graphs for each of the data points through a similarity evaluation of the sigmoid-fitted angle-intensity graphs. and may perform the step of determining each resolution of the inspected lidar device based on the similarity-based alignment distance and the number of data points located between the selected data points within the point cloud.

[0021] According to one embodiment of the present invention, the target comprises a first portion and a second portion, and the reflectance of each of the first portion and the second portion may be different from each other.

[0022] According to one embodiment of the present invention, the target may have a linear boundary formed at the portion where the first portion and the second portion meet each other.

[0023] According to one embodiment of the present invention, the first part and the second part are arranged in a horizontal or vertical direction, and when the first part and the second part are arranged in a horizontal direction, the linear boundary is formed in a vertical direction, and when the first part and the second part are arranged in a vertical direction, the linear boundary can be formed in a horizontal direction.

[0024] According to one embodiment of the present invention, the intensity data included in the data point calculated based on light reflected from the first part may be different from the intensity data included in the data point calculated based on light reflected from the second part.

[0025] According to one embodiment of the present invention, the target is configured in the form of a flat plate, and the first part and the second part can form the target as a single unit.

[0026] The device and method for inspecting each resolution of a lidar device according to the present invention can determine each resolution of a lidar device by using a target comprising at least two parts having different reflectances.

[0027] The device and method for inspecting each resolution of a lidar device according to the present invention can determine each resolution of a lidar device using intensity data included in a point cloud calculated by the lidar device.

[0028] FIG. 1 is a schematic diagram illustrating the operation of a light sensing and distance measuring device or a lidar device to which the present invention is applied.

[0029] FIG. 2 is a drawing showing each resolution inspection device of a lidar device according to one embodiment of the present invention.

[0030] FIG. 3 is a diagram showing a resolution inspection system of a lidar device according to one embodiment of the present invention.

[0031] FIG. 4 is a diagram showing the relationship between the arrival point of light radiated by a lidar device according to one embodiment of the present invention and the data point within the point cloud calculated by the lidar device.

[0032] FIG. 5 is a diagram showing the setting of a region of interest within a point cloud according to one embodiment of the present invention.

[0033] FIG. 6 is a diagram showing that the positional relationship between the light arrival point and the target changes as the lidar device according to one embodiment of the present invention is rotated.

[0034] FIG. 7 is a diagram showing that the position of the light arrival point and the data included in the data point corresponding to the arrival point change as the lidar device according to one embodiment of the present invention is rotated.

[0035] FIG. 8 is a diagram illustrating the operation of acquiring intensity data included in data points according to the rotation angle of the lidar device.

[0036] FIG. 9 is a diagram showing the result of performing the operation described in FIG. 8 on each of two different data points within a point cloud calculated by a lidar device according to one embodiment of the present invention.

[0037] Figure 10 is a diagram showing the result of performing a sigmoid fitting on the angle-strength graph described with reference to Figure 9.

[0038] FIG. 11 is a drawing showing the results of inspecting each resolution of a lidar device by the method for determining each resolution according to the first embodiment described with reference to FIG. 9.

[0039] FIG. 12 is a flowchart illustrating a method for inspecting each resolution of a lidar device according to one embodiment of the present invention.

[0040] Hereinafter, a method and system for inspecting each resolution of a LiDAR device according to an embodiment of the present invention will be described in detail with reference to the attached drawings. However, it will be readily apparent to those skilled in the art that the attached drawings are provided merely to facilitate the disclosure of the contents of the present invention, and that the scope of the present invention is not limited to the scope of the attached drawings.

[0041]

[0042] Introduction

[0043] FIG. 1 is a schematic diagram illustrating the operation of a light sensing and distance measuring device or a lidar device to which the present invention is applied.

[0044] Referring to FIG. 1, a light detection and distance measuring device (100, hereinafter also referred to as a LiDAR device) to which the present invention is applied may include a light emitter (110) for emitting light, a light detector (120) for detecting reflected light that is reflected back from an object (200) after the emitted light, and an optical device (130) provided in the light path radiated and received from the light emitter (110) and the light detector (120). Here, the light emitter (110) may be a diode and a laser light source. The LiDAR device can calculate the range or property of an object (200) using the reflected light that is reflected back from the object (200).

[0045] In this specification, the device subject to inspection may be interchangeably referred to as a lidar device.

[0046] A point cloud refers to a set of data points in 3D space. A set of data points calculated by a LiDAR device (100) to which the present invention is applied can also be called a point cloud. Since the distances between data points constituting the point cloud are generally non-uniform, it is desirable to specifically encode all three coordinates (orthogonal coordinates or spherical coordinates) for each point.

[0047] According to the present invention, the device subject to testing is referred to as the Device Under Test (DUT).

[0048] Among results where the measurement value is positive, the case where the measurement value is accurate—that is, where both the measurement value and the result are positive—is called a True Positive (TP). Among results where the measurement value is positive, the case where the measurement value is inaccurate—that is, where the measurement value is positive but the result is negative—is called a False Positive (FP).

[0049] The probability of valid points in a single measurement and / or multiple accumulated measurements for a single target is called the Probability of Detection (PoD) or True Positive Rate. The probability of detection may depend on background noise, the reflectivity of the target, the tolerance of the range, and other attributes. The PoD can be calculated by the following Equation 1, where True (TP) represents scan points that hit the target in its entirety at distance (actual) ±Δ. The probability of detection is calculated as the ratio of the number of valid points to the number of theoretical points.

[0050] [Mathematical Formula 1]

[0051]

[0052]

[0053] In a point cloud of a LiDAR device, the angle formed by the connection between two adjacent detection points and the 3D coordinate origin of the point cloud in terms of azimuth and elevation angles is called angular resolution. The angular resolution of a LiDAR device can be divided into azimuth resolution and elevation resolution.

[0054] In the point cloud of a LiDAR device, the angle between two outermost effective points where the PoD exceeds 50% (Lambertian target reflectance 50%) is called the field of view. The FOV range includes a horizontal FOV range and a vertical FOV range. The horizontal FOV range and the vertical FOV range may also be referred to as the horizontal angle of view and the vertical angle of view.

[0055] Capturing the entire FOV (horizontal / vertical) is called a frame.

[0056]

[0057] Overall configuration of each resolution inspection device of the LiDAR device

[0058] FIG. 2 is a drawing showing each resolution inspection device of a lidar device according to one embodiment of the present invention.

[0059] As shown in FIG. 2, the inspection device (10) may include a support part (11) for the device to be inspected, a rotation adjustment part (12), a processor part (13), and a memory part (14).

[0060] The support member (11) of the device to be inspected is intended to support the device to be inspected. More specifically, the support member (11) of the device to be inspected can be combined with the device to be inspected to support the device to be inspected, and can rotate together with the device to be inspected by the rotation adjustment member (12) as described below.

[0061] The rotation adjustment unit (12) is for rotating the device to be inspected and the device to be inspected support unit (11). The rotation adjustment unit (12) can be connected to the device to be inspected support unit (11) and can rotate the device to be inspected support unit (11) and / or the device to be inspected.

[0062] The processor unit (13) can control the operation of the rotation adjustment unit (12). Additionally, the processor unit (13) can control the operation of the inspection target device connected to the inspection device (10). As described below, the processor unit (13) can process information output by the inspection target device connected to the inspection device (10) and the rotation adjustment unit (12), and can determine each resolution of the inspection target device by processing the above information.

[0063] The memory unit (14) can store information output by the device to be inspected connected to the inspection device (10). The memory unit (14) can store information generated by the processor unit (14) based on the information output by the device to be inspected. The memory unit (14) can have a program recorded therein to enable the processor unit (13) to perform an operation to control the operation of the rotation adjustment unit (12) and to process the information output by the device to be inspected to determine each resolution of the device to be inspected.

[0064]

[0065] Overall configuration of each resolution inspection system of the LiDAR device

[0066] FIG. 3 is a diagram showing a resolution inspection system of a lidar device according to one embodiment of the present invention.

[0067] Specifically, FIG. 3(a) is a schematic diagram showing the arrangement between the lidar device to be inspected, the inspection device for each resolution of the lidar device, and the target. Also, FIG. 3(b) is a diagram showing the partial reflectance of the target shown in FIG. 3(a).

[0068] As illustrated in FIG. 3(a), each resolution inspection system (1000) of the lidar device (100) may include a lidar device (100) to be inspected, each resolution inspection device (10) of the lidar device (100), and a target (20).

[0069] Specifically, the lidar device (100) can be connected to an inspection device (10). More specifically, the inspection device (10) can control the operation of the connected lidar device (100).

[0070] Specifically, the target (20) may be positioned at a predetermined distance from the lidar device (100) and the inspection device (10). The target (20) may be configured in the form of a flat plate. When the target (20) is configured in the form of a plate, the target (20) may be positioned so that the flat portion faces the lidar device (100). In this case, light emitted by the lidar device (100) in the initial position may be incident perpendicularly on the target (20).

[0071] Specifically, the lidar device (100) can be rotated in a horizontal or vertical direction by the inspection device (10). Additionally, the lidar device (100) can emit light toward a target (20). The emitted light is reflected from the target (20), and the reflected light can be collected and detected by the lidar device (100).

[0072] As shown in FIG. 3(b), the target (20) may include a first part (20a) and a second part (20b).

[0073] Specifically, the first part (20a) and the second part (20b) may have different reflectivity. For example, the first part (20a) may have a reflectivity of A%, and the second part (20b) may have a reflectivity of B%. Here, A may be a value greater than B. That is, the reflectivity of the first part (20a) may be greater than the reflectivity of the second part (20b).

[0074] According to the present invention, the greater the reflectance of the object to which the light emitted by the lidar device (100) is reflected, the greater the intensity of the reflected light reflected from the object. Referring to FIG. 3 (b), the intensity of the reflected light reflected from the first part (20a) may have a greater value than the intensity of the reflected light reflected from the second part (20b).

[0075] According to one embodiment of the present invention, within each resolution inspection system (1000) of the lidar device (100), the lidar device (100) and the target (20) may be arranged with a predetermined initial arrangement relative to each other. Here, the initial arrangement may refer to the arrangement of the lidar device (100) and the target (20) in the first rotation stage when the lidar device (100) to be inspected is rotated in a plurality of rotation stages by the inspection device (10).

[0076] Specifically, the initial arrangement between the lidar device (100) and the target (20) can be set so that light emitted by the lidar device (100) reaches the flat surface of the target (20) in a direction perpendicular to it. Additionally, the lidar device (100) and the target (20) may be arranged apart by a predetermined distance. However, they are not limited thereto.

[0077] According to one embodiment of the present invention, each resolution inspection method of a lidar device may be performed multiple times for a single lidar device (100) to be inspected. Alternatively, each resolution inspection method of a lidar device may be performed for different lidar devices (100) to be inspected. In this case, when the lidar device (100) and the target (20) are placed within the system (1000) with a predetermined initial arrangement relative to each other, the reproductivity of the measurement value for each resolution may be improved. As illustrated in FIG. 3(b), a linear boundary may be formed at the part where the first part (20a) and the second part (20b) of the target (20) meet each other. Referring to FIG. 3(b), the first part (20a) and the second part (20b) may be arranged in a horizontal direction. Although not illustrated in FIG. 3(b), the first part (20a) and the second part (20b) may also be arranged in a vertical direction.

[0078] Specifically, when the first part (20a) and the second part (20b) are arranged in a horizontal direction, the aforementioned linear boundary may be formed in a vertical direction. Additionally, when the first part (20a) and the second part (20b) are arranged in a vertical direction, the aforementioned linear boundary may be formed in a horizontal direction.

[0079]

[0080] Correspondence between optical reach points and data points

[0081] FIG. 4 is a diagram showing the relationship between the arrival point of light radiated by a lidar device according to one embodiment of the present invention and the data point within the point cloud calculated by the lidar device.

[0082] Specifically, FIG. 4(a) shows emitted light emitted toward a predetermined arrival point on a target and reflected light reflected from said arrival point. Additionally, FIG. 4(b) shows a data point calculated based on the reflected light shown in FIG. 4(a) among the data points included in the point cloud calculated by the lidar device.

[0083] As illustrated in FIG. 4(a), the lidar device (100) can emit light toward a target (20). The emitted light can reach a predetermined point of arrival (30) on the target (20) and be reflected.

[0084] A LiDAR device (100) can collect reflected light and produce a point cloud (40) based on the collected light. As shown in FIG. 4(b), the point cloud (40) can be visualized by a specific visualization tool. For example, the visualization tool may be at least one software selected from the group including open source software such as CloudCompare, Meshlab, PCL (Point Cloud Library), and Open3D, and commercial software such as AutoCAD, Bentley Pointools, Leica Cyclone, and Autodesk Recap. However, it is not limited thereto.

[0085] When a LiDAR device (100) emits light toward an area containing a target (20) and calculates a point cloud (40) based on the light reflected therefrom, the point cloud (40) may include a subset (T) corresponding to the target (20). The subset (T) may be composed of a plurality of data points corresponding to the target (20).

[0086] Specifically, the subset (T) may include a first subset (Ta) and a second subset (Tb). For example, the first subset (Ta) may correspond to a first part (20a) of the target (20), and the second subset (Tb) may correspond to a second part (20b) of the target (20).

[0087] Referring to FIG. 4(b), the first subset (Ta) may include a data point (50). The data point (50) may correspond to a light arrival point (30). That is, the data point (50) may be calculated by the lidar device (100) based on light reflected from the light arrival point (30). The data point (50) may include at least one data selected from the group including three-dimensional coordinates for the light arrival point (30), depth information, intensity of reflected light, reflectance, and RGB values.

[0088] FIG. 5 is a diagram illustrating the setting of a region of interest within a point cloud according to an embodiment of the present invention. Specifically, FIG. 5(a) shows a plurality of light arrival points on a target. In addition, FIG. 5(b) visualizes a point cloud including data points corresponding to each of the plurality of light arrival points shown in FIG. 5(a) and displays a predetermined cluster.

[0089] As described above with reference to FIG. 4, the plurality of data points shown in FIG. 5 (b) can each correspond to the plurality of light reaching points shown in FIG. 5 (a).

[0090] Here, the plurality of light arrival points illustrated in FIG. 5(a) refer to a plurality of points where a plurality of lights emitted by the lidar device (100) reach the target (20). For example, the lidar device (100) may emit a plurality of lights through an array-type light emitter (110) composed of a plurality of channels. Also, for example, the lidar device (100) may form a plurality of light arrival points through a light emitter (110) composed of a plurality of channels arranged in a vertical direction and a horizontal scanner. Also, for example, the lidar device (100) may emit a plurality of lights through a light emitter (110) composed of a single channel and a light splitter. However, it is not limited thereto.

[0091] As shown in FIG. 5(b), a predetermined cluster containing at least one data point within a point cloud (40) can be set as a Region of Interest (ROI).

[0092] For example, a region of interest (R1) according to one embodiment may include a single data point.

[0093] In addition, for example, the region of interest (R2) according to another embodiment may include one or more data points formed in a single column in a horizontal or vertical direction.

[0094] In addition, for example, the region of interest (R3) according to another embodiment may include an array or subset containing a plurality of data points.

[0095] According to one embodiment of the present invention, the operation of setting a region of interest within a point cloud (40) can be performed by an inspection device (10). Specifically, the inspection device (10) can track at least one data point included within the set region of interest. More specifically, the fact that the inspection device (10) tracks a data point may mean tracking and identifying the change trend of at least one data selected from a group including three-dimensional coordinates, depth information, intensity of reflected light, reflectance, and RGB values ​​included in the data point within the region of interest.

[0096] According to one embodiment of the present invention, for each data point (50) included in the point cloud (40), a unique horizontal and vertical angle can be defined based on the total field of view of the lidar device (100). Specifically, the unique horizontal and vertical angle based on the total field of view can indicate the position of the individual data point (50) on the point cloud (40). Such unique horizontal and vertical angles can be maintained constant even though the position of the light arrival point (30) corresponding to the data point (50) changes on the target (20) as the lidar device (100) rotates.

[0097] According to one embodiment of the present invention, the inspection device (10) can set a region of interest within a point cloud (40) based on unique horizontal and vertical angles defined based on the entire field of view of the lidar device (100). Specifically, the inspection device (10) can select at least one data point (50) within the point cloud (40) based on unique horizontal and vertical angles and set a region of interest to include the selected data point (50).

[0098] According to one embodiment of the present invention, an inspection device (10) can determine each resolution of a lidar device (100) to be inspected by performing a predetermined calculation method consisting of a plurality of steps. Specifically, the inspection device (10) may be configured to perform the above-described calculation method only for data points (50) included in a set region of interest. By doing so, the information processing speed of the process in which the inspection device (10) determines each resolution can be improved.

[0099] According to one embodiment of the present invention, the inspection device (10) can filter or filter some of the data points (50) included in the point cloud (40) calculated by the LiDAR device (100). Specifically, the inspection device (10) can filter the data points (50) corresponding to the light arrival point (30) located at the edge of the target (20). By filtering the data points (50) where the fluctuation range of the acquired intensity data value may be large, the inspection device (10) can track the data points (50) within the point cloud (40) more stably.

[0100] According to one embodiment of the present invention, the inspection device (10) may perform an additional filtering process on the point cloud (40) calculated by the LiDAR device (100) for more stable tracking of data points (50). For example, the inspection device (10) may perform filtering on the calculated point cloud (40) based on at least one technique selected from the group comprising temporal intensity noise filtering, range consistency filtering, intensity gradient-based edge suppression, signal confidence-based filtering, and angle-based ROI constraint filtering. However, it is not limited thereto.

[0101]

[0102] Movement of the light arrival point due to the rotation of the LiDAR device

[0103] FIG. 6 is a diagram showing that the positional relationship between the light arrival point and the target changes as the lidar device according to one embodiment of the present invention is rotated.

[0104] Specifically, FIG. 6 depicts a situation in which a lidar device (100) is rotated horizontally by an inspection device (10).

[0105] As described above with reference to FIG. 5, the lidar device (100) emits a plurality of lights in a predetermined manner, and the emitted lights can reach a destination point with a predetermined arrangement.

[0106] For example, as shown in FIG. 6(a), at a specific rotational stage, the points of light emitted by the lidar device (100) may have a rectangular arrangement and all of them may be formed on the target (20).

[0107] At this time, as illustrated in FIG. 6 (b) to (e), when the lidar device (100) is rotated by the inspection device (10) in a rotation step different from the rotation step in FIG. 6 (a), at least some of the light arrival points may not be formed on the target (20) and may be formed away from the target (20).

[0108] That is, as the lidar device (100) rotates by the inspection device (10), the point of light arrival can also be changed in its overall position relative to the target (20).

[0109] As illustrated in FIG. 6, a destination point (30) located at a predetermined point among a plurality of destination points formed with a predetermined arrangement can be specified. The absolute position of the destination point (30) on the arrangement of the plurality of destination points may not change despite the overall movement of the plurality of destination points caused by the rotation of the lidar device (100). Accordingly, the destination point (30) may also move on the target (20) along with the overall movement of the plurality of destination points by the rotation of the lidar device (100).

[0110] Although not illustrated in FIG. 6, as the positions of multiple arrival points change overall in relation to the target (20), the data contained in the data points corresponding to each of the multiple arrival points may also change. That is, the three-dimensional coordinate data and intensity data contained in the data points may change.

[0111] For example, as the destination point (30) moves on the target (20), the data included in the data point calculated corresponding to the destination point (30) may also change.

[0112]

[0113] Changes in data included in data points

[0114] FIG. 7 is a diagram showing that the position of the light arrival point and the data included in the data point corresponding to the arrival point change as the lidar device according to one embodiment of the present invention is rotated.

[0115] Specifically, FIG. 7(a) shows that a predetermined arrival point among a plurality of arrival points moves on the target according to the rotation of the lidar device. Additionally, FIG. 7(b) shows that the data contained in the data point changes in response to the movement of the arrival point shown in FIG. 7(a).

[0116] Referring to FIG. 7(a), a predetermined reach point (30) among a plurality of reach points may be specified. As the lidar device (100) rotates, the position of the reach point (30) on the target (20) may change. As shown in FIG. 7(a), the position of the reach point (30) may change sequentially to position (30-1), position (30-2), position (30-3), position (30-4), and position (30-5) according to the rotation step.

[0117] Meanwhile, the lidar device (100) can rotate by a predetermined angle at each rotation step. For example, the lidar device (100) can rotate by 0.01° in the horizontal direction at each rotation step. However, it is not limited thereto.

[0118] In this process, the location of the arrival point (30) can be changed from the first part (20a) of the target (20) to the second part (20b). That is, the arrival point (30) can move past the boundary surface between the first part (20a) and the second part (20b) on the target (20) where the reflectivity changes.

[0119] As illustrated in FIG. 7(b), as the destination point (30) moves on the target (20), the data included in the data point (50) calculated corresponding to the destination point (30) may change.

[0120] For example, if the arrival point (30) is formed at position (30-1), the data point (50-1) may include data regarding the three-dimensional coordinates at position (30-1) on the target (20), the reflectance, and the intensity of the reflected light accordingly.

[0121] For example, if the arrival point (30) is formed at position (30-2), the data point (50-2) may include data regarding the three-dimensional coordinates at position (30-2) on the target (20), the reflectance, and the intensity of the reflected light accordingly.

[0122] For example, if the arrival point (30) is formed at position (30-3), the data point (50-3) may include data regarding the three-dimensional coordinates at position (30-3) on the target (20), the reflectance, and the intensity of the reflected light accordingly.

[0123] For example, if the arrival point (30) is formed at a location (30-4), the data point (50-4) may include data regarding the three-dimensional coordinates at the location (30-4) on the target (20), the reflectance, and the intensity of the reflected light accordingly.

[0124] For example, if the arrival point (30) is formed at a location (30-5), the data point (50-5) may include data regarding the three-dimensional coordinates at the location (30-5) on the target (20), the reflectance, and the intensity of the reflected light accordingly.

[0125]

[0126] Acquisition of strength data according to rotation angle

[0127] Figures 7 and 8 are diagrams for explaining the operation of acquiring intensity data included in data points according to the rotation steps of the lidar device.

[0128] As described above with reference to FIG. 7, when the destination point (30) moves, the intensity data included in the data point (50) corresponding to the destination point (30) may also change.

[0129] Specifically, the intensity data included in the data point (50) may change depending on the movement of the arrival point (30). For example, as shown in FIG. 7, if the arrival point (30) moves past a boundary line on the target (20) where the reflectance changes, the intensity data included in the data point (50) may change. At this time, the intensity data is a predetermined lower limit (I Min ) or upper limit(I max From ) a predetermined upper limit (I max ) or lower limit(I Min It can be gradually changed to ).

[0130] For convenience of explanation, FIG. 8 assumes a case where the reflectance of the first part (20a) on the target (20) corresponding to the first subset (Ta) on the point cloud (40) is smaller than the reflectance of the second part (20b) on the target (20) corresponding to the second subset (Tb). For example, as the inspection target lidar device (100) rotates, the intensity data included in the data point (50) is at a predetermined lower limit (I Min From ) a predetermined upper limit (I MaxIt may be gradually changed to ). However, it is not limited to this.

[0131] In the graph illustrated in FIG. 8, the X-axis represents the value of the rotation angle at each rotation step of the inspection target lidar device (100) by the inspection device (10), and the Y-axis represents the value of the intensity data included in the data point. Specifically, the value of the rotation angle at each rotation step can be expressed in degrees (°). Additionally, the intensity data can be expressed without units. However, it is not limited thereto.

[0132] As illustrated in FIG. 8, as the reach point (30) moves, the value of the intensity data included in the data point (50) corresponding to the reach point (30) can be gradually changed.

[0133] Meanwhile, if the value of the rotation angle of the inspection target lidar device (100) exceeds a predetermined angle, the value of the intensity data included in the data point (50) may not change further despite the movement of the corresponding arrival point (30) in a predetermined section. In the above case, the value of the intensity data is an upper limit (I max It can be understood as ).

[0134] Additionally, if the value of the rotation angle of the inspection target lidar device (100) is less than a predetermined angle, the value of the intensity data included in the data point (50) may not change further despite movement of the corresponding arrival point (30) in a predetermined section. In the above case, the value of the intensity data is a lower limit (I Min It can be understood as ).

[0135] According to one embodiment of the present invention, the inspection device (10) can obtain information about the rotational step of the LiDAR device (100) and strength data included in the data point (50). The graph shown in FIG. 8 visually represents the information about the rotational step obtained by the inspection device (10), that is, the value of the strength data according to the rotation angle.

[0136] Specifically, as described above with reference to FIGS. 5 to 7, the inspection device (10) can track specific data points within the point cloud generated by the lidar device (100) while the lidar device (100) is rotating. More specifically, the inspection device (10) can acquire intensity data included in the data points that change according to the rotation of the lidar device (100).

[0137]

[0138] Each resolution determination

[0139] FIG. 9 is a diagram showing the result of performing the operation described in FIG. 8 on each of two different data points within a point cloud calculated by a lidar device according to one embodiment of the present invention.

[0140] As illustrated in FIG. 9, the inspection device (10) can select at least one of the data points corresponding to a plurality of arrival points where a plurality of lights emitted by the lidar device (100) each reach the target (20). Specifically, the inspection device (10) can select at least one data point formed in the same row or column within the point cloud (40). For example, the inspection device (10) can select data points (50a) and (50b) corresponding to arrival points (30a) and arrival points (30b), respectively. At this time, the inspection device (10) can set the area (Ra) containing the data point (50a) and the area (Rb) containing the data point (50b) as regions of interest.

[0141] According to one embodiment of the present invention, the inspection device (10) can track each selected data point. Specifically, the inspection device (10) can acquire intensity data included in the data points that change as the lidar device (100) rotates.

[0142] For example, referring to FIG. 9, when the inspection device (10) tracks data points (50a) and data points (50b), the inspection device (10) can acquire intensity data included in each of the data points (50a) and data points (50b) according to each rotation step of the lidar device (100).

[0143]

[0144] Method for determining each resolution according to the first embodiment

[0145] According to one embodiment of the present invention, the inspection device (10) has an average value (I) of intensity data based on a point cloud (40) calculated by a lidar device (100). Avg ) can be calculated. Specifically, the average value (I Avg ) is the lower limit (I) described above with reference to FIG. 8. Min ) and upper limit( I Max It can be the average of ).

[0146] According to one embodiment of the present invention, the inspection device (10) uses a linear interpolation technique for each selected data point to obtain the average value (I) of the intensity data. Avg The value of the rotation angle corresponding to ) can be calculated. Specifically, the inspection device (10) can calculate the average value (I) among the values ​​of intensity data included in the data points that change as the lidar device (100) rotates. Avg The smallest value (upper closest value) and the average value (I) among values ​​exceeding ) Avg It is possible to identify the largest value (lower proximity value) among values ​​less than ).

[0147] According to one embodiment of the present invention, the inspection device (10) has the above-described average value (I Avg The smallest value and the average value (I) among values ​​exceeding ) AvgIt can be assumed that the intensity data included in the data point increases linearly with the rotation angle among the largest values ​​among values ​​less than ). In this case, the inspection device (10) calculates the average value (I) of the intensity data for each selected data point through linear regression analysis. Avg The corresponding angle (θ) expected to correspond to ) Corr. The value of ) can be calculated.

[0148] For example, as illustrated in FIG. 9, the inspection device (10) for each of the selected data point (50a) and data point (50b) has a corresponding angle (θ Corr., 1 ) and corresponding angle (θ Corr., 2 ) can be calculated.

[0149] According to one embodiment of the present invention, the inspection device (10) has a calculated corresponding angle (θ Corr Each resolution of the inspection target lidar device (100) can be determined based on ). Each resolution can be calculated by the following [Equation 2].

[0150]

[0151] [Mathematical Formula 2]

[0152]

[0153] (Here,

[0154] θ Corr., 1 = Corresponding angle for the first data point,

[0155] θ Corr., 2 = Corresponding angle for the second data point,

[0156] N = the number of data points formed between the first data point and the second data point)

[0157]

[0158] In [Equation 2], the first data point and the second data point may each be a data point selected by the inspection device (10). The first data point and the second data point may be formed in the same row or the same column within the point cloud (40).

[0159] For example, referring to FIG. 9, each resolution of the lidar device (100) can be calculated as a value of |θCorr., 1 - θCorr., 2| / 2.

[0160] Meanwhile, FIG. 9 describes determining the horizontal angular resolution by rotating the inspection target lidar device (100) in a horizontal direction, but this is merely an example for convenience of explanation and the present invention is not limited thereto. When the inspection target lidar device (100) rotates in a vertical direction, the inspection device (10) according to the present invention may also determine the vertical angular resolution of the inspection target lidar device (100).

[0161]

[0162] Method for determining each resolution according to the second embodiment

[0163] FIG. 10 is a diagram showing the result of performing a sigmoid fitting on the angle-intensity graph described with reference to FIG. 9. Specifically, FIG. 10 (a) illustrates the result of performing a sigmoid fitting on the angle-intensity graph for two different data points. Additionally, FIG. 10 (b) illustrates the parallel translation of one of the sigmoid-fitted angle-intensity graphs along the angle axis.

[0164] According to one embodiment of the present invention, sigmoid fitting may refer to fitting using a mathematical model in the form of an S-shaped curve. Specifically, a sigmoid function may be used for sigmoid fitting. The sigmoid function may be expressed in the form of [Equation 3] below.

[0165] [Mathematical Formula 3]

[0166]

[0167]

[0168] Here, L represents the asymptotic maximum of the function, x0 represents the inflection point of the curve, and k can be a parameter that controls the steepness of the curve. The sigmoid function can mathematically approximate the phenomenon where the response value y gradually increases or decreases depending on the independent variable x, and thus can be used to smoothly connect experimental data and quantitatively analyze trends of change.

[0169] According to one embodiment of the present invention, sigmoid fitting may include the step of performing nonlinear regression analysis on the measured data to optimize the values ​​of parameters L, k, and x0 of the sigmoid function according to [Equation 3].

[0170] As illustrated in FIG. 10 (a), the processor unit (13) of the inspection device (10) can perform sigmoid fitting on an angle-intensity graph for at least one data point (50) included in the point cloud (40) produced by the lidar device (100).

[0171] For example, the processor unit (13) may perform a sigmoid fitting on an angle-intensity graph for data point (50c) and data point (50d). The solid line graph may be a first sigmoid curve generated as a result of the sigmoid fitting on the angle-intensity graph for data point (50c). Additionally, the dotted line graph may be a second sigmoid curve generated as a result of the sigmoid fitting on the angle-intensity graph for data point (50d).

[0172] Here, data point (50c) and data point (50d) are points located on the same horizontal column in the point cloud (40), and N data points (50) may be located between them (where N is a non-negative integer).

[0173] As illustrated in FIG. 10(b), a predetermined area enclosed by the first sigmoid curve (solid line), the second sigmoid curve (dotted line), and the X-axis (angle axis) may have a predetermined area. Here, the size of the area may change when the second sigmoid curve moves parallel to the X-axis (angle axis) direction while the position of the second sigmoid curve remains fixed.

[0174] According to one embodiment of the present invention, the processor unit (13) can generate data for a sigmoid curve corresponding to each of a plurality of data points (50) and perform a similarity evaluation on the generated sigmoid curve. Specifically, the similarity evaluation may mean evaluating the degree to which the shapes of the plurality of sigmoid curves match each other. More specifically, the processor unit (13) can calculate the value of an angle at which each sigmoid curve must move parallel to the X-axis (angle axis) direction on a graph so that the degree to which the plurality of sigmoid curves match each other has a maximum value. The processor unit (13) may set the point where the area of ​​the region enclosed by the plurality of sigmoid curves and the X-axis (angle axis) is maximum as the point where the degree to which the plurality of sigmoid curves match each other has a maximum value. Here, the value of the angle may be referred to as a similarity-based aligned distance. That is, the processor unit (13) can calculate the similarity-based alignment distance through similarity evaluation.

[0175] For example, referring to (b) of FIG. 10, the processor unit (13) can calculate a similarity-based alignment distance between data points (50a) and data points (50b) through a similarity evaluation of the first sigmoid curve and the second sigmoid curve.

[0176] According to one embodiment of the present invention, the inspection device (10) can determine each resolution of the lidar device (100) based on a calculated similarity-based alignment distance. Specifically, each resolution of the lidar device (100) can be determined based on a similarity-based alignment distance calculated for a plurality of data points (50) and the number of data points (50) located between the plurality of data points (50). More specifically, each resolution can be calculated by the following [Equation 4].

[0177] [Mathematical Formula 4]

[0178]

[0179]

[0180] Here, the similarity-based alignment distance can be calculated for two data points (50) included in a point cloud (40) generated by, for example, a LiDAR device (100). The two data points (50) may be located on the same horizontal column of the point cloud (40). Additionally, N other points may be located between the two data points (50) (N is a non-negative integer). However, it is not limited thereto.

[0181]

[0182] According to the present invention, each resolution inspection system (1000) may utilize a target (20) comprising at least two parts with different reflectances. At least two parts with different reflectances may form a single target (20) as a single unit. Thus, a simpler method for inspecting each resolution of a LiDAR device (100) can be performed compared to the case where multiple targets must be prepared.

[0183] Additionally, as the number of targets decreases, the possibility of the inspection result for each resolution of the lidar device (100) changing according to the placement of the targets may decrease.

[0184] According to the present invention, each resolution inspection system (1000) can determine each resolution of the LiDAR device (100) based on the intensity of reflected light from the target (20). At this time, the reflectance of each of two or more parts included in the target (20) can be set without being constrained by spatial constraints. Accordingly, each resolution inspection system (1000) can determine each resolution of the LiDAR device (100) in an environment where the reflectance of each of two or more parts of the target (20) shows a greater difference. In this case, each resolution inspection system (1000) can inspect each resolution of the LiDAR device (100) more precisely.

[0185]

[0186] Experimental data

[0187] FIG. 11 is a drawing showing the results of inspecting each resolution of a lidar device by the method for determining each resolution according to the first embodiment described with reference to FIG. 9.

[0188] Specifically, FIG. 11(a) is a table showing the angle value for each of the 9th and 10th data points in the point cloud calculated by the lidar device, the intensity value calculated from each recorded frame, and the average of the intensity values. Also, FIG. 11(b) shows the angle-intensity graph and the intensity average value for each of the 9th and 10th data points. Additionally, FIG. 11(c) shows the process of determining the angle resolution of the lidar device according to the method described above with reference to FIG. 9.

[0189] In FIG. 11, the experiment was performed using a lidar device (100) to be inspected, an inspection device (10), and a target (20).

[0190] Specifically, the target (20) includes two parts having reflectances of 3% and 95%, respectively.

[0191] Specifically, the specifications of the lidar device (100) to be inspected are as follows.

[0192]

[0193] Scan frequency: 10Hz

[0194] LiDAR Type: S-LiDAR (Solid-state LiDAR)

[0195] Scanning Type: Polygon mirror scanning type

[0196] Angle resolution: 0.18°

[0197]

[0198] In Fig. 11, the 9th data point (9 th Data Point) and the 10th data point (10 th A Data Point is a data point formed in the same row or same column within a point cloud (40) generated by a LiDAR device (100) to be inspected. Specifically, the 9th data point and the 10th data point may be formed adjacent to each other in a horizontal or vertical direction.

[0199] Referring to FIG. 11, the operation described with reference to FIG. 2 to FIG. 9 was performed for the 9th data point and the 10th data point using the inspection device (10) according to the present invention.

[0200] Accordingly, as shown in Fig. 11 (c), it was confirmed that the angular resolution of the lidar device (100) under inspection has a value of 0.179424°. That is, it was confirmed that the similarity between the angular resolution of the lidar device (100) under inspection determined by the inspection device (10) and the actual angular resolution value (0.18°) is very high.

[0201]

[0202] Each resolution inspection method

[0203] FIG. 12 is a flowchart illustrating a method for inspecting each resolution of a lidar device according to one embodiment of the present invention.

[0204] As illustrated in FIG. 12, the method for inspecting each resolution of a lidar device (100) may include the steps of: preparing and positioning the lidar device (100) to be inspected and the target (20) (S110); rotating the lidar device (100) to be inspected and causing the lidar device (100) to record at least one frame at each rotation step and to calculate a point cloud (40) based on the recorded frame (S130); selecting a plurality of data points (50) within the calculated point cloud (40) (S150); acquiring intensity data at least in part of the rotation step for each selected data point (50) (S170); and determining each resolution of the lidar device (100) to be inspected based on the acquired intensity data and the rotation angle at the rotation step in which the intensity data was acquired (S190).

[0205] Regarding step (S110), details of the inspection target lidar device (100) and target (20) are as described above.

[0206] In relation to step (S130), the details regarding the correspondence between the unit rotation angle of the inspection target lidar device (100), the light arrival point (30), and the data point (50) are as described above.

[0207] Regarding step (S150), details of the multiple data points (50) selected are as described above.

[0208] According to one embodiment of the present invention, step (S150) may include setting at least one region of interest within the calculated point cloud (40) and selecting a plurality of data points from the set region of interest. However, the present invention is not limited thereto, and may include any inspection method that selects data points (50) directly within the calculated point cloud (40) without separately performing the step of setting a region of interest.

[0209] Regarding step (S170), details of the intensity data of reflected light included in each selected data point (50) are as described above.

[0210] Regarding step (S190), details of the method for determining each resolution of the inspection target lidar device (100) based on intensity data and rotation angle are as described above.

[0211]

[0212] Although the present invention described above has been explained with reference to the embodiments illustrated in the drawings, this is merely illustrative, and those skilled in the art will understand that various modifications and variations of the embodiments are possible therefrom. However, such modifications should be considered to be within the technical scope of protection of the present invention. Accordingly, the true technical scope of protection of the present invention should be determined by the technical spirit of the appended claims.

[0213] [Explanation of the symbol]

[0214] 10: Inspection device

[0215] 11: Support for the device under inspection

[0216] 12: Rotation adjustment section

[0217] 13: Processor section

[0218] 14: Memory section

[0219] 20 : Target

[0220] 20a : Part 1

[0221] 20b : Part 2

[0222] 30: Light reach point

[0223] 30-1 : Location

[0224] 30-2 : Location

[0225] 30-3 : Location

[0226] 30-4 : Location

[0227] 30-5 : Location

[0228] 40: Point cloud

[0229] 50: Data points

[0230] 50-1 : Data points

[0231] 50-2 : Data points

[0232] 50-3 : Data points

[0233] 50-4 : Data points

[0234] 50-5 : Data points

[0235] 100: LiDAR device

[0236] 110 : Photoeer

[0237] 120 : Photodetector

[0238] 130 : Optical device

[0239] 200 : Object

[0240] T : subset

[0241] Ta : 1st subset

[0242] Tb : 2nd subset

[0243] R1: Region of interest

[0244] R2: Region of interest

[0245] R3: Region of Interest

[0246] S110: Each resolution inspection method of the lidar device (100) involves the step of preparing and placing the lidar device (100) to be inspected and the target (20).

[0247] S130: A step of rotating the inspection target lidar device (100), causing the inspection target lidar device (100) to record at least one frame at each rotation step, and calculating a point cloud (40) based on the recorded frame.

[0248] S150: A step of selecting multiple data points (50) within the calculated point cloud (40).

[0249] S170: For each selected data point (50), a step of obtaining intensity data in at least part of the rotation step.

[0250] S190: A step of determining each resolution of the inspection target lidar device (100) based on the acquired strength data and the rotation angle at the rotation step in which the strength data was acquired.

Claims

1. In a method for inspecting each resolution of a LiDAR (Light Detection And Ranging) device, Step of preparing and deploying the LiDAR device and target to be inspected; A step of rotating the above-mentioned lidar device to be inspected in rotational steps, causing the above-mentioned lidar device to record at least one frame at each of the rotational steps, and calculating a point cloud based on the recorded frame; A step of selecting multiple data points within the calculated point cloud; For each of the selected data points, a step of acquiring intensity data in at least some of the rotation steps; For each of the above data points, a step of calculating the average value of the acquired intensity data; For each of the above data points, a step of selecting an upper proximity value and a lower proximity value for the calculated average value among the acquired intensity data; For each of the above data points, a step of calculating a corresponding angle corresponding to the average value through linear regression analysis of the rotation angle in the rotation step for each of the selected upper proximity value and the lower proximity value and the upper proximity value and the lower proximity value; and A step of determining each resolution of the inspected LiDAR device based on the corresponding angle calculated for each of the above data points and the number of data points located between the selected data points within the point cloud; including, Method for inspecting each resolution of a LiDAR device.

2. In a method for inspecting each resolution of a LiDAR (Light Detection And Ranging) device, Step of preparing and deploying the LiDAR device and target to be inspected; A step of rotating the above-mentioned lidar device to be inspected in rotational steps, causing the above-mentioned lidar device to record at least one frame at each of the rotational steps, and calculating a point cloud based on the recorded frame; A step of selecting multiple data points within the calculated point cloud; For each of the selected data points, a step of acquiring intensity data in at least some of the rotation steps; For each of the above data points, a step of generating an angle-intensity graph based on the acquired intensity data and the rotation angle at the rotation step in which the intensity data was acquired; A step of performing sigmoid fitting on the angle-intensity graph generated above; A step of calculating a similarity-based aligned distance between the sigmoid-fitted angle-intensity graphs for each of the data points through a similarity evaluation of the sigmoid-fitted angle-intensity graphs; and A step of determining each resolution of the inspected LiDAR device based on the similarity-based alignment distance and the number of data points located between the selected data points within the point cloud; including, Method for inspecting each resolution of a LiDAR device.

3. In Paragraph 1 or 2, The above target includes a first part and a second part, and The reflectances of the first part and the second part, respectively, are different from each other. Method for inspecting each resolution of a LiDAR device.

4. In Paragraph 3, The above target is such that a linear boundary is formed at the point where the first part and the second part meet each other. Method for inspecting each resolution of a LiDAR device.

5. In Paragraph 4, The first part and the second part are arranged in a horizontal or vertical direction, and When the first part and the second part are arranged in a horizontal direction, the linear boundary is formed in a vertical direction, and When the first part and the second part are arranged in a vertical direction, the linear boundary is formed in a horizontal direction. Method for inspecting each resolution of a LiDAR device.

6. In Paragraph 3, The intensity data included in the data point calculated based on light reflected from the first part is different from the intensity data included in the data point calculated based on light reflected from the second part. Method for inspecting each resolution of a LiDAR device.

7. In Paragraph 3, The above target is configured in the form of a flat plate, and The first part and the second part together form the target. Method for inspecting each resolution of a LiDAR device.

8. In a resolution inspection system for a LiDAR (Light Detection And Ranging) device, An inspection device for determining each resolution of the above-mentioned inspection target lidar device; and A target for reflecting light emitted by the above-mentioned inspection target lidar device; Includes, The above inspection device is, A support member for a device to be inspected for supporting the above-mentioned lidar device to be inspected; A rotation adjustment unit for rotating the above-mentioned inspection target device support and the above-mentioned inspection target lidar device in rotational steps; and A processor unit for controlling the operation of the above-mentioned inspection target lidar device and the above-mentioned rotation adjustment unit, and for determining each resolution of the above-mentioned inspection target lidar device based on intensity data included in a point cloud calculated by the above-mentioned inspection target lidar device; including, Each resolution inspection system of the LiDAR device.

9. In Paragraph 8, The above processor unit is, A step of causing the rotation adjustment unit to rotate the inspection target lidar device according to the rotation steps, causing the inspection target lidar device to record at least one frame at each of the rotation steps, and calculating the point cloud based on the recorded frames; A step of selecting multiple data points within the point cloud calculated above; For each of the selected data points, a step of acquiring the intensity data in at least some of the rotation steps; For each of the above data points, a step of calculating the average value of the acquired intensity data; For each of the above data points, a step of selecting an upper proximity value and a lower proximity value for the calculated average value among the acquired intensity data; For each of the above data points, a step of calculating a corresponding angle corresponding to the average value through linear regression analysis of the rotation angle in the rotation step for each of the selected upper proximity value and the lower proximity value and the upper proximity value and the lower proximity value; and A step of determining each resolution of the inspected LiDAR device based on the corresponding angle calculated for each of the above data points and the number of data points located between the selected data points within the point cloud; is intended to perform, Each resolution inspection system of the LiDAR device.

10. In Paragraph 8, The above processor unit is, A step of causing the rotation adjustment unit to rotate the inspection target lidar device according to the rotation steps, causing the inspection target lidar device to record at least one frame at each of the rotation steps, and calculating the point cloud based on the recorded frames; A step of selecting multiple data points within the point cloud calculated above; For each of the selected data points, a step of acquiring the intensity data in at least some of the rotation steps; For each of the above data points, a step of generating an angle-intensity graph based on the acquired intensity data and the rotation angle at the rotation step in which the intensity data was acquired; A step of performing sigmoid fitting on the angle-intensity graph generated above; A step of calculating a similarity-based aligned distance between the sigmoid-fitted angle-intensity graphs for each of the data points through a similarity evaluation of the sigmoid-fitted angle-intensity graphs; and A step of determining each resolution of the inspected LiDAR device based on the similarity-based alignment distance and the number of data points located between the selected data points within the point cloud; is intended to perform, Each resolution inspection system of the LiDAR device.

11. In Paragraph 9 or 10, The above target includes a first part and a second part, and The reflectances of the first part and the second part, respectively, are different from each other. Each resolution inspection system of the LiDAR device.

12. In Paragraph 11, The above target is such that a linear boundary is formed at the point where the first part and the second part meet each other. Each resolution inspection system of the LiDAR device.

13. In Paragraph 12, The first part and the second part are arranged in a horizontal or vertical direction, and When the first part and the second part are arranged in a horizontal direction, the linear boundary is formed in a vertical direction, and When the first part and the second part are arranged in a vertical direction, the linear boundary is formed in a horizontal direction. Each resolution inspection system of the LiDAR device.

14. In Paragraph 11, The intensity data included in the data point calculated based on light reflected from the first part is different from the intensity data included in the data point calculated based on light reflected from the second part. Each resolution inspection system of the LiDAR device.

15. In Paragraph 11, The above target is configured in the form of a flat plate, and The first part and the second part together form the target. Each resolution inspection system of the LiDAR device.

Images